The present invention relates to the field of computer processing of fingerprint images. More specifically the invention relates systems and methods for identifying and removing one or more scar regions in a fingerprint image. A fingerprint image with scar regions removed is further processed in an Automatic Fingerprint Identification System (AFIS). An AFIS is used to identify and verify a person by means of their fingerprint.
Current methods and systems for removing scars in an acquired fingerprint image are lacking and insufficient in that they do not quickly, accurately, efficiently, or effectively allow correction of fingerprint images, resulting in false matches and false verification and identification of a person.
It is known in this art that scar lines hinder the ability of AFIS to match an acquired fingerprint image to a reference fingerprint image. Attempts for compensating for the major scar lines in an image have been reported in the literature. For example, a spatial domain based inpainting technique using a diffusion matrix to reconstruct broken ridges was proposed by Oliveira, et al., in “Fast Digital Imaging Repainting,” International Conference on Visualization, Imaging, and Image Processing (VIIP 2001), 2001. Gottschlich, et al., “Robust Orientation Field Estimation and Extrapolation Using Semilogical Line Sensors,” Information Forensics and Security, IEEE Transactions, vol. 4, no. 4, pp. 802-811, December 2009, presented a line-sensor based method to estimate the flow of ridges and valleys for removing scar.
Yau, et al., “Enhancing Oriented Pattern using Adaptive Directional FFT Filter, IEEE 2nd International Conference on Information, Communication & Signal Processing, Singapore, December 1999, discussed reconstructing the oriented ridge patterns in an image. Sulong, et al., “A new Scar Removal Technique of fingerprint images” in ICIC-BME, 2009 proposed a directional filter which strengthens the ridge pattern as they belong to a dominant local orientation, while suppressing the scar lines as it is oriented against the dominant direction. This method used a band pass directional filter to remove the uneven background and to suppress high-frequency noise. This method is based on the incorrect assumption that fingerprints exhibit everywhere a well-defined local ridge orientation. Although the scheme was successful to diminish the scar lines at some places, it was not able to eliminate them completely from the image.
Digital inpainting techniques are commonly used to reconstruct small damaged portions of an image, for example in applications such as reconstructing scans of deteriorated images by removing scratches or stains, removing text and logos from still images or videos, or creating artistic effects. Most inpainting methods work by first selecting the image regions which need inpainting and then the known image information is used to fill in the missing areas by propagating inward from the region boundaries. In order to produce a good reconstruction, an inpainting technique should attempt to continue lines of equal gray value as smoothly as possible inside the reconstructed region. In Bertalmio et al., “Image Painting,” in SIGGRAPH 2000, Computer Graphics Proceedings, Annual Conference Series, 2000, pp. 417-424, and Bertalmio, et al., “Navier-stokes, fluid dynamics, and image and video inpainting,” in ICCV 2001, 2001, pp. 1335-1362, the image smoothness information is propagated along the isophotes directions, estimated by the image gradient rotated 90 degrees. Image Laplacian is used to calculate the gradient. Later, Telea, in “An image inpainting technique based on the fast marching method,” Journal of Graphics Tools, vol. 9, no. 1, 2004, pp. 23-34, proposed a new technique for inpainting by propagating an image smoothness estimate along the image gradient. The missing regions are treated as level sets and a fast marching method is used to propagate the image information.